Enterprises are increasingly capturing, storing, and mining a plethora of information related to communications with their customers. Often this information is stored and indexed within databases. Once the information is indexed, queries are developed on an as-needed basis to mine the information from the database for a variety of organizational goals: such as planning, analytics, reporting, etc.
Often an analyst associated with an enterprise has a business problem to solve or business question to answer that entails analyzing information from the enterprise's database. Acquisition of selective information is probably a first and cursory step in the overall analytical process that the analyst needs to follow in order to solve the business problem or answer the business question. The selective information may itself be queried and mined for certain predefined characteristics or attributes. Once these results are obtained, the analyst may want to further perform some calculation against the data that conforms to the predefined characteristics. Yet, modern database interfaces do not permit such fine-grain calculations to be achieved in an automated manner for the analyst. Consequently, an analyst may have to enlist the services of a programmer or may have to manually calculate items of interest before a desired business question can be properly answered.
Thus, it can be seen that improved mechanisms for applying calculations within a database environment are desirable.